A case study of one-to-two mapping fuzzy PD controllers on inverted pendulum

Shao, Huihe; Hu, Bin; Zhu, Zhida

doi:10.1109/fuzzy.1999.793277

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…One of the intelligent techniques, fuzzy logic developed by Zadeh [10,11] is applied for controller design in many applications [10,11]. A fuzzy logic controller (FLC) was proved analytically to be equivalent to a nonlinear PI controller when a nonlinear defuzzification method is used [12].…”

Section: Figure I Outdoor Rcs Labmentioning

confidence: 99%

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Fuzzy Logic Controller for Enhancing RCS's Lab Measurements

Galal¹,

Wang²

2016

Proceedings of the 2016 International Conference on Advanced Materials Science and Environmental Engineering

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Precise and accurate radar cross section (RCS) measurements, especially for tracking small radar cross section targets (e.g. tracks on Fighters), or RCS reduction and radar absorbing materails evaluation for other targets of interest such as aircraft, tanks, or ships, is a must. As a consequence, the need of having more accurate evaluation for the RCS of the targets is required. This paper demonstrates the existing RCS's Lab. Then, discusses the automation of the RCS's antenna holder movements, using fuzzy logic, to have better target tracking while measurement process, in order to suppress the unwanted manmade error. Taking into account the fuzzy nature of human decision making processes and real-time properties, this paper has established different fuzzy controllers then tested and compared with a crisp decision system. The first one has been developed using an expert knowledge, the second one was learned from the recorded videos.

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Section: Figure I Outdoor Rcs Labmentioning

confidence: 99%

“…In the existing lab, Vision tracking was accomplished by using a joystick to track the target maneuvers as shown in figure (1). To track while measurement process, in order to suppress the unwanted man made error, an online nonlinear controller for nonlinear tracking should be used [9,10].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Controller for Enhancing RCS's Lab Measurements

Galal¹,

Wang²

2016

Proceedings of the 2016 International Conference on Advanced Materials Science and Environmental Engineering

View full text Add to dashboard Cite

show abstract

“…One of the intelligent techniques, is fuzzy logic and had been developed by Zadeh [10], [11] is applied for controller design in many applications [10], [11]. A fuzzy logic controller (FLC) was proved analytically to be equivalent to a nonlinear PI controller when a nonlinear defuzzification method is used [12].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and Automating of RCS’s Lab Tracker

Galal¹,

Wang²

2016

IJMO

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Abstract-Radar cross section measurement must be precise and accurate especially for tracking small radar cross section targets (e.g. tracks on Fighters); other targets of interest may be aircraft, tanks, or ships. As a consequence, the need of having more accurate evaluation for the Radar Cross Section (RCS) of the targets is required. This paper describes and demonstrates the modeling/automation of the RCS's antenna holder movements. In order to suppress the unwanted manmade error, fuzzy logic controller was used, to have better target tracking while measurement process. Taking into account the fuzzy nature of human decision making processes and real-time properties, this paper has established different fuzzy controllers then tested and compared with a crisp decision system. The first one has been developed using an expert knowledge, the second one was learned from the recorded videos.Index Terms-Fuzzy logic control, multi-input/ multi output, nonlinear system, RCS lab measurements enhancement, and video guidance.

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Fuzzy Logic Control for video terminally guided system

Galal

Wang

2014

Proceedings of the 33rd Chinese Control Conference

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High precision control is desirable for future weapon systems. Numerous control design methodologies are developed for a real-time automatic system capable of tracking two-dimensional (2-D) targets in complex scenes. The design objective of the control system is to achieve a rapid and precise response capable of tracking the fire control commands under the influences of disturbances, nonlinearities, and modeling uncertainties. A mathematical model of 2-D image spatial and temporal evolution applicable to certain classes of targets and target perturbations is developed. A Fuzzy Logic Controller (FLC) scheme is proposed to control the multi-body, multi-input and multi output nonlinear systems with joints represented by a turret-barrel model which consists of two subsystems: two motors driving two loads (turret and barrel) coupled by nonlinear dynamics. Simulation results verify the desired system tracking performance. Then, as a verification and demonstration, the designed FLC is implemented into a PICC microcontroller to control a Dc motor.

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A case study of one-to-two mapping fuzzy PD controllers on inverted pendulum

Cited by 5 publications

References 14 publications

Fuzzy Logic Controller for Enhancing RCS's Lab Measurements

Fuzzy Logic Controller for Enhancing RCS's Lab Measurements

Modeling and Automating of RCS’s Lab Tracker

Fuzzy Logic Control for video terminally guided system

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